Month April 2014

iPad sales were unexpectedly slow in Q1. Tim Cook explained it as follows:

iPad sales came in at the high end of our expectations, but we realized they were below analysts’ estimates and I would like to proactively address why we think there was a difference. We believe almost all of the difference can be explained by two factors.

First, in the March quarter last year we significantly increased iPad channel inventory, while this year we significantly reduced it.

Second, we ended the December quarter last year with a substantial backlog of iPad mini that was subsequently shipped in the March quarter whereas we ended the December quarter this year near supply demand balance.

We continue to believe that the tablet market will surpass the PC market in size within the next few years, and we believe that Apple will be a major beneficiary of this trend.

Tim Cook went on to say “over two-thirds of people registering an iPad in the last six months were new to iPad”

In a later discussion, Luca Maestri said:

As Tim explained earlier, our iPad results and the comparison to the March quarter last year were heavily influenced by channel inventory changes. Specifically, this year we sold 16.4 million iPad into our channel and sold through almost 17.5 million, reducing our channel inventory by 1.1 million units.

Last year, we sold over 19.4 million iPads into our channels and sold through 18 million, and therefore increased channel inventory by 1.4 million units. As a result, the year-over-year sell through decline was only 3% compared to the sell-in decline of 16%.

We exit the March quarter with 5.1 million of iPad channel inventory which left us within our target range of four to six weeks. iPad continues to lead all other tablet by far in terms of user engagement, size of ecosystem, customer satisfaction and e-commerce.

In the postmodern computing world that we live in, the measure of success isn’t revenue or profit or units sold but the number of users that an ecosystem can attract. Therefore the monthly active user (MAU) unit of performance seems to be in vogue right now. E.g.:

Facebook claims Messenger has more than 200 million MAUs

WhatsApp has 500 million MAUs, 48 million of whom are in India

Line last month announced that it had 400 million users (active or not)

WeChat claimed 355 million MAUs

Viber claims 105 million MAUs

Startups are aggregating these millions of MAUs in order to obtain valuations for raising capital[1] and the faster the growth in MAUs the more “successful” the company is considered.

When companies are acquired it’s common to take the transaction value and divide it by MAUs to get an idea of “what an user is worth”. This is because there are no revenues to measure and MAUs are taken as a proxy. However, the process by which a MAU becomes a dollar of profit is, to put it kindly, circuitous.

For most (all?) it’s not yet clear how it happens especially since not all MAUs are created equal and MAU loyalties can change rapidly and if we added all the projected revenues each MAU will contribute to each app on her device we might reach some absurdity. In actuality, today, for the companies listed above, there are no revenues at all directly from their services.

In violation of this convention, there are some companies which manage to obtain revenues from their users. Two such are Apple and Amazon. In the last quarter Apple reported having 800 million iTunes accounts.[2] These aren’t MAUs since the activity level is not noted, but we do know how much is spent on iTunes and services. In addition, Amazon cites 244 million active customer accounts representing accounts which generated purchases within the last 12 months.

This allows us to compare Apple and Amazon in terms of accounts, revenue per account, and, via some analysis, even profitability per account.

The following graphs tell this story. First, the total number of accounts:

Note that I added trend lines to both graphs and their formulas.

The following are the revenue per account for iTunes (further broken into estimated iTunes segment revenues per account.) and for Amazon. Note that the vertical scales are different.

Notes:

It’s been said that it’s difficult to get funded with only 10 million MAUs [↩]

adding, for some unknown reason, that most of them have credit cards. [↩]

“Innovation” is one of those words that, through casual overuse, has come to signify a wide array of distinct concepts – in some sense, the word is literally losing definition, like an out-of-focus photograph that manages to become blurrier every time you look at it.

These days, anytime anyone does something vaguely new, or a new feature gets added to some gadget or other, the innovation word gets flung about. Indeed, the word is used with the same reckless abandon as those other favourites of jargon-loving MBA types, “solutions” and “disruption”, rendering it increasingly meaningless.

After n quarters of predictability, Apple surprised with sales performance that was 3.74% above the top of their guidance. This may not seem significant but since instituting a new range-bound guidance method in Q1 of last year the company reported revenue within about 1% of the top of the range.

This is in stark contrast to the wide variance in prior years. The following graph shows the “error” in guidance as the percent difference between reported sales and guidance[1].

So prior to last quarter we were lulled into thinking that guidance was very nearly perfectly predicting the company. As I tweeted, it took the “sport” out of trying to do any forecasting. All an analyst had to do is tweak the main product growth figures to hit the sales target and then subtract the (generously provided) operating expenses and (also provided) tax rate to get the earnings. Only unknown to getting to an estimate of EPS was how many shares would still be outstanding.[2]

Knowing Apple also means that average selling prices are also very rigidly set in stone so the degrees of freedom in analysis were becoming highly constrained.

But just when you think you spotted a pattern, it changes. The company surprised with performance outside the band. The following graph shows the estimate ranges it has given and the actual revenues delivered.[3]

In Part 1 of a look at Google’s future I showed that Google’s revenues have been highly correlated with the population of Internet users in the markets it serves. If there were a causal relationship between population of users and revenue growth then the company would face a growth inflection point when that population becomes half penetrated.

In Significant Digits Episode 1 (Part 1) I showed data which suggests that the inflection point will come in 2016. Essentially the argument is that Google’s growth is ultimately limited by the population of users and that itself is a predictable number. I also used the example of the PC and smartphone penetration curves to show how the perception of the fortunes of companies whose revenues are based on those technologies were affected by inflections in their respective adoptions.

However, correlation is not causation. These users we count are not the customers who pay for Google’s services. Users (or usage) is therefore only a proxy. It may be a good proxy and intuitively it makes sense that it’s a driver of growth but fundamentally the company lives on a stream of revenues paid by advertisers[1]. In order to really evaluate the opportunity we need to “follow the money” and track down where it comes from.

We don’t have visibility into the exact sources of these revenues but we have a top-level geographic segmentation (shown below.)

Notes:

This is true to date and certainly it could change but hints of how that might change are still not visible to me [↩]

This week Myke is joined by Horace Dediu. They discuss his work at Nokia and how that lead to starting his blog, Asymco. They also talk about the role and work of an analyst, his presentation series – Airshow – and graphs, naturally.

Illiteracy is the inability to read and write. Though the percent of sufferers has halved in the last 35 years, currently 15% of the world has this affliction. Innumeracy is the inability to apply simple numerical concepts. The rate of innumeracy is unknown but chances are that it affects over 50% of us. This tragedy impedes our ability to have a discourse on matters related to quantitative judgement while policy decisions increasingly depend on this judgement.

But there is another form of ignorance which seems to be universal: the inability to understand the concept and role of innovation. The way this is exhibited is in the misuse of the term and the inability to discern the difference between novelty, creation, invention and innovation. The result is a failure to understand the causes of success and failure in business and hence the conditions that lead to economic growth.

My contribution to solving this problem is to coin a word: I define innoveracy as the inability to understand creativity and the role it plays in society. Hopefully identifying individual innoveracy will draw attention to the problem enough to help solve it.

“Lastly, nationally circulating tabloid Ilta-Sanomat gets a look at Nokia’s fabled tablet computer that was developed nine years before the iPad hit the market. According to the paper, Nokia had its own innovative tablet device ready in 2001, but unfortunately it never made it to the shops. A former Nokia expert Esko Yliruusi says that the project was suspended a heartbeat before the tablet hit the market because it was thought that there was insufficient demand for such a device.”[1]

To explain what’s wrong with this usage we need some definitions.

The definition of innovation is easy to find but it’s one thing to read the definition and another to understand its meaning. Rather than defining it again, I propose using a simple taxonomy of related activities that put it in context.

Novelty: Something new

Creation: Something new and valuable

Invention: Something new, having potential value through utility

Innovation: Something new and uniquely useful

The taxonomy is illustrated with the following diagram. The position of the circles shows the embedding of meaning[2]

To illustrate further, here are some examples of the concepts.

Novelties: The choice of Gold as a color for the iPhone; the naming of a version of Android as “Kit Kat”; coining a new word.

Creations: The fall collection of a fashion designer; a new movie; a blog post.

Inventions: Anything described by a patent; The secret formula for Coca Cola.

The differences are also evident in the mechanisms that exist to protect the works:

Novelties are usually not protectable but since their value is very limited the copying is not seen to cause harm.

Creations are protected by copyright or trademark but are not patentable since they lack utility.

Inventions can be protected for a limited time through patents but can also be protected indefinitely by being kept secret. Their uniqueness may also be the means by which they can be kept a secret.

Innovations can be protected through market competition but are not defensible through legal means.

Note that the taxonomy has a hierarchy. Creations are novel, inventions are creations and innovations are usually based on some invention. However inventions are not innovations and neither are creations or novelties. Innovations are therefore the most demanding works because they require all the conditions in the hierarchy. Innovations implicitly require defensibility through a unique “operating model”. Put another way, they remain unique because few others can copy them.

To be innovative is very difficult, but because of the difficulty, being innovative is usually well rewarded. Indeed, it might be easier to identify innovations simply by their rewards. It’s almost a certainty that any great business is predicated on an innovation and that the lack of a reward in business means that some aspect of the conditions of innovation were not met.

The causal, if-and-only-if connection with reward is what should be the innovation litmus test. If something fails to change the world (and hence is unrewarded) you can be pretty sure it was not innovative enough.

Which brings us to the quote above. The fact that the Nokia tablet of 2001 not only did not succeed in the market but was not even released implies that it could not have been innovative. The product was only at the stage of perhaps being an invention (if it can be shown to be unique) or merely a creation (if it isn’t.) Furthermore, if the product is so poorly designed that it is literally unusable then it is just a novelty. A design, sketch or verbal description might be novel but it does not qualify as an innovation or an invention or even a creation. How far the depiction went toward making a dent in the universe defines its innovativeness.

Why does this matter?

Understanding that innovation requires passing a market test and that passing that test is immensely rewarding both for the creator and for society at large means that we can focus on how to make it happen. Obsessing over the mere novelties or inventions means we allocate resources which markets won’t reward. Misusing the term and confusing it with activities that don’t create value takes our eye off the causes and moves us away from finding ways of repeatably succeeding.

Recognizing that innoveracy is a problem allows us to address it. Addressing it would mean we could speak a language of value creation that everyone understands.

In this inaugural episode we open with the biggest question facing the biggest technological innovation of our time: the limit to growth of the Internet. The Internet is the backbone of our post-industrial society as much as the railroad was the backbone of the industrial revolution. Even more so, the diffusion of internet consumption is the fundamental engine of growth at a time when industrial economies are all mired in syndromes of underinvestment and misallocation of resources.

And so it matters greatly if and when the Internet will “inflect” in growth, going from acceleration to deceleration. Mobile computing sustained this acceleration, bringing computing and connectivity to the billions for whom the PC would always be beyond reach. But even with the expansion of device-based usage limits are in sight.

The implications could be profound. Frothy valuations and optimism could evaporate. Venture Capital could find few exits and the “second Internet Bubble” could burst. On the other hand, maybe the data shows that opportunity is largely unmet. Quantity of users is but one proxy. How can growth and business model innovation continue?

To help us think this through I have as my guest Marko Anderson, cofounder of Random[1] and a former colleague at Nokia.

Stay tuned for four more parts:

Part 2: Browsing vs. Apps The HTML5 vs. Native debate and the jobs the Internet is hired to do.

Part 3: Monetize This The problem with business model innovation. When the ad dollars run out, what will take their place?

Part 4: Random How discovery is changing and the value of irrationality.

Part 5: Glass is half full How can we screw this up? Privacy, Surveillance and The Internet Citizen’s Bill of Rights.

Significant Digits is a talk show where we take time to recognize patterns in the lives of technologies.